postgres-mcp-server

analyze_workload_indexes

Identify slow queries from database workload using pg_stat_statements and suggest indexes to minimize execution time.

Instructions

Analyze database workload and recommend indexes. Uses pg_stat_statements to find slow queries and suggests indexes to improve them.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "analyze_workload_indexes"
  }
}

Input Schema

Name	Required	Description	Default
`topQueriesCount`	No	Number of top queries to analyze (1-50)
`includeHypothetical`	No	Test recommendations with hypothetical indexes (requires hypopg)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.0.3May 30, 2026

TDQS

A3.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'recommend indexes' implying read-only, but does not explicitly confirm no mutation, required permissions, or potential side effects. The mechanism (pg_stat_statements) is disclosed, but safety profile is vague.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no redundant information. First sentence states core purpose, second adds technical mechanism. Efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema or annotations, the description adequately explains purpose and mechanism but lacks details on return format, error handling (e.g., missing hypopg), and behavioral traits like read-only nature. Sibling tools like analyze_query_indexes create ambiguity that could be clarified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for both parameters. The description adds value by explaining that includeHypothetical requires hypopg extension, which is not in the schema. This extra context helps correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verb 'Analyze' and 'recommend', clearly identifies the resource (database workload and indexes), and distinguishes from siblings like analyze_db_health and analyze_query_indexes by mentioning pg_stat_statements and slow queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for index recommendations but does not explicitly state when to use this tool vs alternatives like analyze_query_indexes. No exclusions or prerequisites are mentioned, leaving the agent to infer context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.